DocumentCode :
1955160
Title :
New practices for railway condition monitoring and predictive analysis
Author :
Swift, M. ; Aurisicchio, G. ; Pace, P.
Author_Institution :
MERMEC UK Ltd., Derby, UK
fYear :
2011
fDate :
29-30 Nov. 2011
Firstpage :
1
Lastpage :
6
Abstract :
Condition data play a fundamental role not only in the control of railway assets oriented towards safety, e.g. identification of potential failures, but also for decision support, improving the assertive power in planning optimized maintenance and renewal works. Railway condition monitoring and predictive analysis oriented to the optimisation of maintenance can be achieved by collection of a wide range of data and related analysis to satisfy both maintenance planning and control requirements, mainly involving the preparation of the maintenance plans and the final checking of the executed activities outcomes. A set of best practices and user requirements for assessing the current asset condition and related optimization of maintenance are described.
Keywords :
condition monitoring; maintenance engineering; optimisation; process control; process planning; railways; asset condition assessment; decision support; failure; maintenance control; maintenance planning; optimisation; railway condition monitoring; railway predictive analysis; condition-monitoring; maintenance; management; railway;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Railway Condition Monitoring and Non-Destructive Testing (RCM 2011), 5th IET Conference on
Conference_Location :
Derby
Type :
conf
DOI :
10.1049/cp.2011.0578
Filename :
6191846
Link To Document :
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